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--- |
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language: |
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- es |
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tags: |
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- generated_from_trainer |
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datasets: |
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- jpherrerap/competencia2 |
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model-index: |
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- name: ner-bert-base-spanish-wwm-uncased |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ner-bert-base-spanish-wwm-uncased |
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This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on the jpherrerap/competencia2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5112 |
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- Body Part Precision: 0.0 |
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- Body Part Recall: 0.0 |
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- Body Part F1: 0.0 |
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- Body Part Number: 0 |
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- Disease Precision: 0.0 |
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- Disease Recall: 0.0 |
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- Disease F1: 0.0 |
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- Disease Number: 0 |
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- Family Member Precision: 0.0 |
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- Family Member Recall: 0.0 |
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- Family Member F1: 0.0 |
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- Family Member Number: 0 |
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- Medication Precision: 0.0 |
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- Medication Recall: 0.0 |
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- Medication F1: 0.0 |
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- Medication Number: 0 |
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- Procedure Precision: 0.0 |
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- Procedure Recall: 0.0 |
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- Procedure F1: 0.0 |
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- Procedure Number: 0 |
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- Overall Precision: 0.0 |
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- Overall Recall: 0.0 |
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- Overall F1: 0.0 |
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- Overall Accuracy: 0.6713 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 13 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Body Part Precision | Body Part Recall | Body Part F1 | Body Part Number | Disease Precision | Disease Recall | Disease F1 | Disease Number | Family Member Precision | Family Member Recall | Family Member F1 | Family Member Number | Medication Precision | Medication Recall | Medication F1 | Medication Number | Procedure Precision | Procedure Recall | Procedure F1 | Procedure Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:-------------------:|:----------------:|:------------:|:----------------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:-------------------:|:----------------:|:------------:|:----------------:|:-----------------:|:--------------:|:----------:|:----------------:| |
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| 0.3372 | 1.0 | 1004 | 1.5112 | 0.0 | 0.0 | 0.0 | 0 | 0.0 | 0.0 | 0.0 | 0 | 0.0 | 0.0 | 0.0 | 0 | 0.0 | 0.0 | 0.0 | 0 | 0.0 | 0.0 | 0.0 | 0 | 0.0 | 0.0 | 0.0 | 0.6713 | |
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| 0.1611 | 2.0 | 2008 | 1.7235 | 0.0 | 0.0 | 0.0 | 0 | 0.0 | 0.0 | 0.0 | 0 | 0.0 | 0.0 | 0.0 | 0 | 0.0 | 0.0 | 0.0 | 0 | 0.0 | 0.0 | 0.0 | 0 | 0.0 | 0.0 | 0.0 | 0.6705 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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